STY: Whitespaces placed at the beginning instead at the end of a line

pandas/core/arrays/categorical.py

@@ -2404,8 +2404,8 @@ def isin(self, values):
         if not is_list_like(values):
             values_type = type(values).__name__
             raise TypeError(
-                "only list-like objects are allowed to be passed"
-                f" to isin(), you passed a [{values_type}]"
+                "only list-like objects are allowed to be passed "
+                f"to isin(), you passed a [{values_type}]"
             )
         values = sanitize_array(values, None, None)
         null_mask = np.asarray(isna(values))

pandas/core/arrays/datetimes.py

@@ -234,11 +234,10 @@ def __init__(self, values, dtype=_NS_DTYPE, freq=None, copy=False):
             values = values._data
 
         if not isinstance(values, np.ndarray):
-            msg = (
+            raise ValueError(
                 f"Unexpected type '{type(values).__name__}'. 'values' must be "
                 "a DatetimeArray ndarray, or Series or Index containing one of those."
             )
-            raise ValueError(msg)
         if values.ndim not in [1, 2]:
             raise ValueError("Only 1-dimensional input arrays are supported.")
 
@@ -249,20 +248,18 @@ def __init__(self, values, dtype=_NS_DTYPE, freq=None, copy=False):
             values = values.view(_NS_DTYPE)
 
         if values.dtype != _NS_DTYPE:
-            msg = (
-                "The dtype of 'values' is incorrect. Must be 'datetime64[ns]'."
-                f" Got {values.dtype} instead."
+            raise ValueError(
+                "The dtype of 'values' is incorrect. Must be 'datetime64[ns]'. "
+                f"Got {values.dtype} instead."
             )
-            raise ValueError(msg)
 
         dtype = _validate_dt64_dtype(dtype)
 
         if freq == "infer":
-            msg = (
+            raise ValueError(
                 "Frequency inference not allowed in DatetimeArray.__init__. "
                 "Use 'pd.array()' instead."
             )
-            raise ValueError(msg)
 
         if copy:
             values = values.copy()

pandas/core/arrays/period.py

@@ -297,8 +297,8 @@ def __arrow_array__(self, type=None):
                 # ensure we have the same freq
                 if self.freqstr != type.freq:
                     raise TypeError(
-                        "Not supported to convert PeriodArray to array with different"
-                        f" 'freq' ({self.freqstr} vs {type.freq})"
+                        "Not supported to convert PeriodArray to array with different "
+                        f"'freq' ({self.freqstr} vs {type.freq})"
                     )
             else:
                 raise TypeError(

pandas/core/computation/expr.py

@@ -466,8 +466,8 @@ def _maybe_evaluate_binop(
 
         if res.has_invalid_return_type:
             raise TypeError(
-                f"unsupported operand type(s) for {res.op}:"
-                f" '{lhs.type}' and '{rhs.type}'"
+                f"unsupported operand type(s) for {res.op}: "
+                f"'{lhs.type}' and '{rhs.type}'"
             )
 
         if self.engine != "pytables":

pandas/core/generic.py

@@ -265,8 +265,8 @@ def _validate_dtype(self, dtype):
             # a compound dtype
             if dtype.kind == "V":
                 raise NotImplementedError(
-                    "compound dtypes are not implemented"
-                    f" in the {type(self).__name__} constructor"
+                    "compound dtypes are not implemented "
+                    f"in the {type(self).__name__} constructor"
                 )
 
         return dtype
@@ -8993,11 +8993,10 @@ def tshift(
                 new_data = self._data.copy()
                 new_data.axes[block_axis] = index.shift(periods)
             elif orig_freq is not None:
-                msg = (
-                    f"Given freq {freq.rule_code} does not match"
-                    f" PeriodIndex freq {orig_freq.rule_code}"
+                raise ValueError(
+                    f"Given freq {freq.rule_code} does not match "
+                    f"PeriodIndex freq {orig_freq.rule_code}"
                 )
-                raise ValueError(msg)
         else:
             new_data = self._data.copy()
             new_data.axes[block_axis] = index.shift(periods, freq)

pandas/core/indexes/base.py

@@ -4790,8 +4790,8 @@ def get_slice_bound(self, label, side, kind):
 
         if side not in ("left", "right"):
             raise ValueError(
-                f"Invalid value for side kwarg, must be either"
-                f" 'left' or 'right': {side}"
+                "Invalid value for side kwarg, must be either "
+                f"'left' or 'right': {side}"
             )
 
         original_label = label

pandas/core/indexes/multi.py

@@ -1288,8 +1288,8 @@ def _get_level_number(self, level) -> int:
                 if level < 0:
                     orig_level = level - self.nlevels
                     raise IndexError(
-                        f"Too many levels: Index has only {self.nlevels} levels,"
-                        f" {orig_level} is not a valid level number"
+                        f"Too many levels: Index has only {self.nlevels} levels, "
+                        f"{orig_level} is not a valid level number"
                     )
             # Note: levels are zero-based
             elif level >= self.nlevels:
@@ -2171,8 +2171,8 @@ def reorder_levels(self, order):
         order = [self._get_level_number(i) for i in order]
         if len(order) != self.nlevels:
             raise AssertionError(
-                f"Length of order must be same as number of levels ({self.nlevels}),"
-                f" got {len(order)}"
+                f"Length of order must be same as number of levels ({self.nlevels}), "
+                f"got {len(order)}"
             )
         new_levels = [self.levels[i] for i in order]
         new_codes = [self.codes[i] for i in order]
@@ -2527,8 +2527,8 @@ def slice_locs(self, start=None, end=None, step=None, kind=None):
     def _partial_tup_index(self, tup, side="left"):
         if len(tup) > self.lexsort_depth:
             raise UnsortedIndexError(
-                f"Key length ({len(tup)}) was greater than MultiIndex lexsort depth"
-                f" ({self.lexsort_depth})"
+                f"Key length ({len(tup)}) was greater than MultiIndex lexsort depth "
+                f"({self.lexsort_depth})"
             )
 
         n = len(tup)

pandas/core/series.py

@@ -1404,8 +1404,8 @@ def to_string(
         # catch contract violations
         if not isinstance(result, str):
             raise AssertionError(
-                "result must be of type str, type"
-                f" of result is {repr(type(result).__name__)}"
+                "result must be of type str, type "
+                f"of result is {repr(type(result).__name__)}"
             )
 
         if buf is None:

pandas/io/common.py

@@ -406,8 +406,8 @@ def get_handle(
                     raise ValueError(f"Zero files found in ZIP file {path_or_buf}")
                 else:
                     raise ValueError(
-                        "Multiple files found in ZIP file."
-                        f" Only one file per ZIP: {zip_names}"
+                        "Multiple files found in ZIP file. "
+                        f"Only one file per ZIP: {zip_names}"
                     )
 
         # XZ Compression

pandas/io/parsers.py

@@ -906,8 +906,8 @@ def _get_options_with_defaults(self, engine):
                         pass
                     else:
                         raise ValueError(
-                            f"The {repr(argname)} option is not supported with the"
-                            f" {repr(engine)} engine"
+                            f"The {repr(argname)} option is not supported with the "
+                            f"{repr(engine)} engine"
                         )
             else:
                 value = _deprecated_defaults.get(argname, default)

pandas/tests/arrays/categorical/test_operators.py

@@ -97,8 +97,8 @@ def test_comparisons(self):
         # comparison (in both directions) with Series will raise
         s = Series(["b", "b", "b"])
         msg = (
-            "Cannot compare a Categorical for op __gt__ with type"
-            r" <class 'numpy\.ndarray'>"
+            "Cannot compare a Categorical for op __gt__ with type "
+            r"<class 'numpy\.ndarray'>"
         )
         with pytest.raises(TypeError, match=msg):
             cat > s
@@ -265,8 +265,8 @@ def test_comparisons(self, data, reverse, base):
         # categorical cannot be compared to Series or numpy array, and also
         # not the other way around
         msg = (
-            "Cannot compare a Categorical for op __gt__ with type"
-            r" <class 'numpy\.ndarray'>"
+            "Cannot compare a Categorical for op __gt__ with type "
+            r"<class 'numpy\.ndarray'>"
         )
         with pytest.raises(TypeError, match=msg):
             cat > s

pandas/tests/computation/test_eval.py

@@ -274,9 +274,9 @@ def check_operands(left, right, cmp_op):
     def check_simple_cmp_op(self, lhs, cmp1, rhs):
         ex = f"lhs {cmp1} rhs"
         msg = (
-            r"only list-like( or dict-like)? objects are allowed to be"
-            r" passed to (DataFrame\.)?isin\(\), you passed a"
-            r" (\[|')bool(\]|')|"
+            r"only list-like( or dict-like)? objects are allowed to be "
+            r"passed to (DataFrame\.)?isin\(\), you passed a "
+            r"(\[|')bool(\]|')|"
             "argument of type 'bool' is not iterable"
         )
         if cmp1 in ("in", "not in") and not is_list_like(rhs):
@@ -408,9 +408,9 @@ def check_compound_invert_op(self, lhs, cmp1, rhs):
         ex = f"~(lhs {cmp1} rhs)"
 
         msg = (
-            r"only list-like( or dict-like)? objects are allowed to be"
-            r" passed to (DataFrame\.)?isin\(\), you passed a"
-            r" (\[|')float(\]|')|"
+            r"only list-like( or dict-like)? objects are allowed to be "
+            r"passed to (DataFrame\.)?isin\(\), you passed a "
+            r"(\[|')float(\]|')|"
             "argument of type 'float' is not iterable"
         )
         if is_scalar(rhs) and cmp1 in skip_these:

pandas/tests/frame/indexing/test_indexing.py

@@ -447,8 +447,8 @@ def test_setitem(self, float_frame):
         tm.assert_series_equal(series, float_frame["col6"], check_names=False)
 
         msg = (
-            r"\"None of \[Float64Index\(\[.*dtype='float64'\)\] are in the"
-            r" \[columns\]\""
+            r"\"None of \[Float64Index\(\[.*dtype='float64'\)\] are in the "
+            r"\[columns\]\""
         )
         with pytest.raises(KeyError, match=msg):
             float_frame[np.random.randn(len(float_frame) + 1)] = 1
@@ -1039,9 +1039,9 @@ def test_getitem_setitem_float_labels(self):
 
         # positional slicing only via iloc!
         msg = (
-            "cannot do slice indexing on"
-            r" <class 'pandas\.core\.indexes\.numeric\.Float64Index'> with"
-            r" these indexers \[1.0\] of <class 'float'>"
+            "cannot do slice indexing on "
+            r"<class 'pandas\.core\.indexes\.numeric\.Float64Index'> with "
+            r"these indexers \[1.0\] of <class 'float'>"
         )
         with pytest.raises(TypeError, match=msg):
             df.iloc[1.0:5]

pandas/tests/frame/test_api.py

@@ -382,8 +382,8 @@ def test_swapaxes(self):
         tm.assert_frame_equal(df.T, df.swapaxes(1, 0))
         tm.assert_frame_equal(df, df.swapaxes(0, 0))
         msg = (
-            "No axis named 2 for object type"
-            r" <class 'pandas.core(.sparse)?.frame.(Sparse)?DataFrame'>"
+            "No axis named 2 for object type "
+            r"<class 'pandas.core(.sparse)?.frame.(Sparse)?DataFrame'>"
         )
         with pytest.raises(ValueError, match=msg):
             df.swapaxes(2, 5)

pandas/tests/frame/test_constructors.py

@@ -1854,9 +1854,9 @@ def check(df):
             # No NaN found -> error
             if len(indexer) == 0:
                 msg = (
-                    "cannot do label indexing on"
-                    r" <class 'pandas\.core\.indexes\.range\.RangeIndex'>"
-                    r" with these indexers \[nan\] of <class 'float'>"
+                    "cannot do label indexing on "
+                    r"<class 'pandas\.core\.indexes\.range\.RangeIndex'> "
+                    r"with these indexers \[nan\] of <class 'float'>"
                 )
                 with pytest.raises(TypeError, match=msg):
                     df.loc[:, np.nan]

pandas/tests/frame/test_dtypes.py

@@ -897,15 +897,15 @@ def test_astype_to_incorrect_datetimelike(self, unit):
 
         df = DataFrame(np.array([[1, 2, 3]], dtype=dtype))
         msg = (
-            r"cannot astype a datetimelike from \[datetime64\[ns\]\] to"
-            r" \[timedelta64\[{}\]\]"
+            r"cannot astype a datetimelike from \[datetime64\[ns\]\] to "
+            r"\[timedelta64\[{}\]\]"
         ).format(unit)
         with pytest.raises(TypeError, match=msg):
             df.astype(other)
 
         msg = (
-            r"cannot astype a timedelta from \[timedelta64\[ns\]\] to"
-            r" \[datetime64\[{}\]\]"
+            r"cannot astype a timedelta from \[timedelta64\[ns\]\] to "
+            r"\[datetime64\[{}\]\]"
         ).format(unit)
         df = DataFrame(np.array([[1, 2, 3]], dtype=other))
         with pytest.raises(TypeError, match=msg):

pandas/tests/indexes/common.py

@@ -37,8 +37,8 @@ class Base:
     def test_pickle_compat_construction(self):
         # need an object to create with
         msg = (
-            r"Index\(\.\.\.\) must be called with a collection of some"
-            r" kind, None was passed|"
+            r"Index\(\.\.\.\) must be called with a collection of some "
+            r"kind, None was passed|"
             r"__new__\(\) missing 1 required positional argument: 'data'|"
             r"__new__\(\) takes at least 2 arguments \(1 given\)"
         )

pandas/tests/indexes/datetimes/test_constructors.py

@@ -644,8 +644,8 @@ def test_constructor_dtype(self):
         )
 
         msg = (
-            "cannot supply both a tz and a timezone-naive dtype"
-            r" \(i\.e\. datetime64\[ns\]\)"
+            "cannot supply both a tz and a timezone-naive dtype "
+            r"\(i\.e\. datetime64\[ns\]\)"
         )
         with pytest.raises(ValueError, match=msg):
             DatetimeIndex(idx, dtype="datetime64[ns]")

pandas/tests/indexes/multi/test_analytics.py

@@ -334,8 +334,8 @@ def test_numpy_ufuncs(idx, func):
     else:
         expected_exception = TypeError
         msg = (
-            "loop of ufunc does not support argument 0 of type tuple which"
-            f" has no callable {func.__name__} method"
+            "loop of ufunc does not support argument 0 of type tuple which "
+            f"has no callable {func.__name__} method"
         )
     with pytest.raises(expected_exception, match=msg):
         func(idx)

pandas/tests/indexes/period/test_indexing.py

@@ -409,8 +409,8 @@ def test_get_loc(self):
             idx0.get_loc(1.1)
 
         msg = (
-            r"'PeriodIndex\(\['2017-09-01', '2017-09-02', '2017-09-03'\],"
-            r" dtype='period\[D\]', freq='D'\)' is an invalid key"
+            r"'PeriodIndex\(\['2017-09-01', '2017-09-02', '2017-09-03'\], "
+            r"dtype='period\[D\]', freq='D'\)' is an invalid key"
         )
         with pytest.raises(TypeError, match=msg):
             idx0.get_loc(idx0)
@@ -434,8 +434,8 @@ def test_get_loc(self):
             idx1.get_loc(1.1)
 
         msg = (
-            r"'PeriodIndex\(\['2017-09-02', '2017-09-02', '2017-09-03'\],"
-            r" dtype='period\[D\]', freq='D'\)' is an invalid key"
+            r"'PeriodIndex\(\['2017-09-02', '2017-09-02', '2017-09-03'\], "
+            r"dtype='period\[D\]', freq='D'\)' is an invalid key"
         )
         with pytest.raises(TypeError, match=msg):
             idx1.get_loc(idx1)

pandas/tests/indexes/test_numeric.py

@@ -188,8 +188,8 @@ def test_constructor_invalid(self):
 
         # invalid
         msg = (
-            r"Float64Index\(\.\.\.\) must be called with a collection of"
-            r" some kind, 0\.0 was passed"
+            r"Float64Index\(\.\.\.\) must be called with a collection of "
+            r"some kind, 0\.0 was passed"
         )
         with pytest.raises(TypeError, match=msg):
             Float64Index(0.0)